1. Field of the Invention
The present invention relates to an image alignment device, method, and program which perform alignment between two 3D images obtained by imaging a target organ of a patient in different phases of respiration, and to a method of generating a 3D deformation model for use in alignment.
2. Description of the Related Art
In image diagnosis using two 3D images acquired by imaging an object at different viewpoints using the same imaging device or different imaging devices, a non-rigid registration technique in which a transformation function (B-spline transformation function or the like) which matches the spatial positions of the object in both images with each other is estimated when both images are superimposed and one or both of the images are deformed using the estimated transformation function to align the two images is known.
David Mattes; David R. Haynor; Hubert Vesselle; Thomas K. Lewellyn; William Eubank, “Non-rigid multimodality image registration”, Proc. SPIE 4322, Medical Imaging 2001: Image Processing, pp. 1609-1620 suggests a method which sets a plurality of control points at predetermined intervals inside an image space, determines the amount of displacement of the control points with the largest similarity between one image and another image deformed by displacing the positions of the control points using a quasi-Newton method, in particular, a limited memory Broyden Fletcher Goldfarb Shanno with boundaries (L-BFGS-B) method, and estimates a B-spline transformation function based on the amount of displacement of the control points at this time. According to this method, it is possible to perform very close local alignment on the two images with a comparatively small shift of the whole images.
JP2002-324238A discloses a method which, in alignment of two images with a comparatively large shift of the whole images, performs a linear transformation process (affine transformation or the like) of parallel movement, rotation, or enlargement and reduction on one image prior to close local alignment and performs rough alignment of the whole images in advance, thereby improving the accuracy of the local alignment.